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Build Optimization

  • 39 installs
  • 28 repo stars
  • Updated June 29, 2026
  • nickcrew/claude-ctx-plugin

Helps with ai & agent building tasks.

About

build-optimization is a Claude Code skill for ai & agent building. It helps solo builders move faster with AI-assisted development.

  • build-optimization
  • AI & Agent Building
  • AI-coding skill

Build Optimization by the numbers

  • 39 all-time installs (skills.sh)
  • Ranked #8,260 of 16,556 AI & Agent Building skills by installs in the Skillselion catalog
  • Data as of Aug 4, 2026 (Skillselion catalog sync)
npx skills add https://github.com/nickcrew/claude-ctx-plugin --skill build-optimization

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Listed on Skillselion
Installs39
repo stars28
Last updatedJune 29, 2026
Repositorynickcrew/claude-ctx-plugin

What it does

Helps with ai & agent building tasks.

Files

SKILL.mdMarkdownGitHub ↗

Build Optimization

Expert guidance for optimizing build systems, reducing compilation times, maximizing cache hit rates, and building developer tools that enhance productivity across the development lifecycle.

When to Use This Skill

  • Diagnosing slow build times and identifying bottlenecks
  • Configuring caching strategies (local, remote, distributed)
  • Setting up incremental builds and parallel execution
  • Optimizing CI/CD pipeline performance and cost
  • Designing or improving bundle splitting and tree shaking
  • Building CLIs, plugins, code generators, or IDE extensions
  • Configuring monorepo tooling (Nx, Turborepo, Bazel)
  • Reducing developer feedback loop times (hot reload, watch mode)
  • Managing build artifacts and reproducibility

Quick Reference

TaskLoad reference
Compilation, caching, incremental builds, CI/CD optimizationskills/build-optimization/references/build-systems.md
Plugin systems, code generation, linting, IDE integration, monorepo toolingskills/build-optimization/references/developer-tooling.md

Core Targets

  • Build time under 30 seconds for development builds
  • Rebuild time under 5 seconds with watch mode
  • Cache hit rate above 90% in CI
  • Zero flaky builds in production pipelines
  • Reproducible builds across environments

Workflow

1. Performance Analysis

Profile the current build before making changes.

  • Measure cold build, incremental rebuild, and hot reload times
  • Profile CPU, memory, and I/O during builds
  • Map the dependency graph and identify bottlenecks
  • Evaluate cache hit rates and invalidation patterns
  • Review current tool configuration for missed optimizations

2. Optimization

Apply targeted improvements based on profiling data.

  • Enable incremental compilation and caching
  • Configure parallel execution across available cores
  • Set up code splitting and tree shaking
  • Optimize module resolution and source transformation
  • Implement remote or distributed caching for CI

3. Tooling

Build or configure developer tools for fast feedback loops.

  • Configure watch mode and hot module replacement
  • Set up clear error messages and progress indicators
  • Integrate build analytics and performance dashboards
  • Add pre-commit hooks for format, lint, and validation

4. Monitoring

Track build health over time.

  • Set up automated build time tracking and alerting
  • Monitor cache hit rates and bundle size trends
  • Detect performance regressions in CI
  • Review and optimize periodically based on data

Common Mistakes

  • Optimizing without profiling first
  • Disabling caching due to intermittent issues instead of fixing invalidation
  • Running full builds when incremental builds would suffice
  • Not parallelizing independent build tasks
  • Ignoring I/O as a bottleneck (disk speed, network latency)
  • Letting bundle sizes grow unchecked without analysis
  • Using a single build configuration for development and production

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